Key Responsibilities
Data Operations & Incident Management
Lead and coordinate the end-to-end incident management lifecycle for data-related production issues.
Drive timely incident resolution, root cause analysis (RCA), and preventive action planning.
Act as the primary escalation point for critical and high-priority BAU incidents.
Monitor data pipelines, interfaces, ETL/ELT processes, data quality issues, and platform performance.
Ensure compliance with SLA, KPI, and operational governance requirements
Coordinate workload planning, resource allocation, and on-call support activities.
Stakeholder Management & Communication
Collaborate closely with Data Custodians, Business Users, Application Support Teams, and Vendors to troubleshoot and resolve data issues.
Liaise with business users to understand impacts, prioritize remediation activities, and provide timely status updates.
Prepare executive-level communications and provide concise updates to senior management during major incidents.
Facilitate incident review meetings, service review discussions, and governance forums.
Data Migration & Project Delivery
Lead and support data migration projects involving data extraction, transformation, validation, reconciliation, and cutover activities.
Coordinate with business, technology, and vendor teams to ensure successful project execution.
Develop migration strategies, implementation plans, rollback procedures, and testing approaches.
Oversee data validation and reconciliation activities to ensure data integrity during migrations.
Data Governance & Quality Management
Support data governance initiatives and ensure adherence to enterprise data standards.
Work with data owners and data custodians to improve data quality, lineage, and stewardship processes.
Implement controls and monitoring mechanisms to identify and prevent recurring data issues.
Maintain operational documentation, runbooks, support procedures, and knowledge repositories.
Identify recurring issues and drive automation opportunities to reduce manual effort and improve reliability.
Job Requirements
Bachelor's Degree or above in Computer Science, Information Technology, Data Engineering, Data Science, Business Analytics, or a related discipline.
Minimum 8+ years of experience in Data Engineering, Data Operations, Production Support, Data Warehousing, or Enterprise Data Management.
Strong analytical, problem-solving, and decision-making skills.
Proven experience managing mission-critical production supports environments and leading end-to-end incident management processes.
Demonstrated experience in leading data migration, data transformation, and enterprise data integration initiatives.
Experience managing teams of Data Custodians, Data Analysts, Data Support Engineers, or related functions.
Strong stakeholder management experience, including engagement with senior business leaders and executive management.
Experience working in Retail, Consumer Goods, Fashion, Luxury Retail is highly preferred.
Understanding of retail KPIs, customer data platforms (CDP), loyalty programs, omnichannel customer journeys, and store operations data is highly desirable.
Experience supporting regional or global data platforms across multiple Asia-Pacific markets is advantageous.
Fluency in both English and Mandarin/Cantonese (written and spoken)
Proficiency in Korean is highly desirable.
Technical Skills
Strong SQL and database troubleshooting skills.
Hands-on experience with enterprise data platforms and cloud data technologies.
Experience with ETL/ELT tools and data integration frameworks.
Knowledge of data governance, metadata management, and data quality frameworks.
Experience with Salesforce, Salesforce Marketing Cloud or Heroku platforms.
Familiarity with Azure, AWS, Databricks, Snowflake, Synapse, or Google Cloud Platform.
Experience using ServiceNow, Jira, Azure DevOps, or similar ITSM platforms.
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关于高知特 (Cognizant)
高知特(Cognizant)（纳斯达克代码：CTSH）作为一家AI Builder和相关技术服务提供商，致力于通过打造全栈AI解决方案，帮助企业将人工智能投资转化为实际价值。公司凭借深厚的行业经验、流程优化和工程技术专长，将企业独特的业务场景融入科技系统，赋能组织释放人才潜能，推动切实成果，并帮助全球企业在瞬息万变的环境中保持领先。如需了解更多详情，敬请访问 cognizant.ai 或关注@cognizant。
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